Lan K K, Wittes J
Biostatistics Research Branch, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20892.
Biometrics. 1988 Jun;44(2):579-85.
This paper considers the problem of monitoring slowly accruing data from a nonsequentially designed experiment. We describe the use of the B-value, which is a transformed Z-value, for the calculation of conditional power. In data monitoring, interim Z-values do not allow simple projections to the end of the study. Moreover, because of their popular association with P-values, Z-values are often misinterpreted. If observed trends are viewed as the realization of a Brownian motion process, the B-value and its decomposition allow simple extrapolations to the end of the study under a variety of hypotheses. Applications are presented to one- and two-sample Z-tests, the two-sample Wilcoxon rank sum test, and the log-rank test.
本文考虑了监测来自非序贯设计实验的缓慢积累数据的问题。我们描述了使用B值（它是一种变换后的Z值）来计算条件功效。在数据监测中，中期Z值不允许简单地推算到研究结束。此外，由于它们与P值密切相关，Z值常常被误解。如果将观察到的趋势视为布朗运动过程的实现，那么在各种假设下，B值及其分解允许简单地推算到研究结束。文中给出了单样本和两样本Z检验、两样本Wilcoxon秩和检验以及对数秩检验的应用。
